Sample Size Determination for Multivariate Performance Analysis with Complex Designs

  • Stefano Bonnini
  • Livio Corain
  • Luigi Salmaso
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)


The literature of multiple comparison methods addresses the problem of ranking treatment groups from best to worst. However, there is no clear indication of how to deal with the information from pairwise multiple comparisons, particularly in the case of blocking (or stratification) or in the case of multivariate response variables. In the present paper we take three methods into consideration to produce a performance ranking of C treatments under study. By means of a simulation study, it is possible to calculate the percentages of correct classifications of the compared methods and study their performances. The proposed simulation study also allows us to determine the minimum sample size useful for detecting performance differences among treatments.


Global Score Complex Design Score Vector Multivariate Statistical Model Sample Size Determination 
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The authors wish to thank the University of Padova (CPDA088513/08 and CPDA092350/09) and the Italian Ministry for University and Research (2008WKHJPK 002) for providing the financial support for this research.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Department of MathematicsUniversity of FerraraFerraraItaly
  2. 2.Department of Management and EngineeringUniversity of PadovaPadovaItaly

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